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Sensors 2012, 12(3), 2766-2786; doi:10.3390/s120302766
Article

The Performance Analysis Based on SAR Sample Covariance Matrix

Received: 30 January 2012; in revised form: 15 February 2012 / Accepted: 24 February 2012 / Published: 1 March 2012
(This article belongs to the Section Remote Sensors)
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Abstract: Multi-channel systems appear in several fields of application in science. In the Synthetic Aperture Radar (SAR) context, multi-channel systems may refer to different domains, as multi-polarization, multi-interferometric or multi-temporal data, or even a combination of them. Due to the inherent speckle phenomenon present in SAR images, the statistical description of the data is almost mandatory for its utilization. The complex images acquired over natural media present in general zero-mean circular Gaussian characteristics. In this case, second order statistics as the multi-channel covariance matrix fully describe the data. For practical situations however, the covariance matrix has to be estimated using a limited number of samples, and this sample covariance matrix follow the complex Wishart distribution. In this context, the eigendecomposition of the multi-channel covariance matrix has been shown in different areas of high relevance regarding the physical properties of the imaged scene. Specifically, the maximum eigenvalue of the covariance matrix has been frequently used in different applications as target or change detection, estimation of the dominant scattering mechanism in polarimetric data, moving target indication, etc. In this paper, the statistical behavior of the maximum eigenvalue derived from the eigendecomposition of the sample multi-channel covariance matrix in terms of multi-channel SAR images is simplified for SAR community. Validation is performed against simulated data and examples of estimation and detection problems using the analytical expressions are as well given.
Keywords: multi-channel systems; sample eigenvalues; Wishart distribution; MIMO; maximum eigenvalue; SAR multi-channel systems; sample eigenvalues; Wishart distribution; MIMO; maximum eigenvalue; SAR
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Erten, E. The Performance Analysis Based on SAR Sample Covariance Matrix. Sensors 2012, 12, 2766-2786.

AMA Style

Erten E. The Performance Analysis Based on SAR Sample Covariance Matrix. Sensors. 2012; 12(3):2766-2786.

Chicago/Turabian Style

Erten, Esra. 2012. "The Performance Analysis Based on SAR Sample Covariance Matrix." Sensors 12, no. 3: 2766-2786.



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